12-01, 21:00–21:30 (UTC), Talk Track I
For video advertisers, precisely hitting their ad performance goals is critical. Undershooting on campaign viewability objectives means spending money on ads that nobody watches, while overshooting them can mean vastly reducing the available ad slots. At JW Player, we combine predictive models with PID controllers to tune decision thresholds and deliver the maximum possible reach to our advertisers while hitting their goals.
At JW Player, we have created a thriving video advertising marketplace that empowers our publishers to monetize their video content and advertisers to identify high-quality and targeted ad opportunities. This requires balancing the trade-off between maximizing ad-engagement as well as campaign scale. We combine predictive and historical models and PID controllers to ensure that the ad opportunities we pass on precisely match our advertisers’ goals.
Here, we describe the PID controllers we use to tune the decision thresholds on our models, the advantages and limitations of this system, and the cascade of controllers we have designed to address such issues. We have many distinct PID controllers deployed, providing daily updates to the decision thresholds for several hundred million daily predictions. We discuss the deployment, performance, and monitoring of these controllers, and our plans for future improvements.
No technical knowledge is expected from the attendees - all concepts will be explained.
No previous knowledge expected
Emily is a Sr Data Scientist at JW Player, the largest video player on the open web, where she has worked since January 2021. Prior to this, Emily was a research seismologist, studying deep Earth structure using earthquake data.